optimization of fuzzy membership functions via pso and ga with application to quad rotor

Quad rotor is a renowned under-actuated unmanned aerial vehicle (uav) with widespread military and civilian applications. despite its simple structure, the vehicle suffers from inherent instability. therefore, control designers always face a formidable challenge in their stabilization and control goal. in this paper, the fuzzy membership functions of the quad rotor fuzzy controllers are optimized using nature-inspired algorithms such as particle swarm optimization (pso) and genetic algorithm (ga). finally, the results of the proposed methods are compared, and a trajectory is defined to verify the effectiveness of the designed fuzzy controllers based on the algorithm with better results.